SAS for Automation of DIFM Customer Propensity Analysis
Fresh reports from Forrester Research released in Q2, 2022 on the subjects of customer analytics and real-time interaction management amplify the present day importance of brands exploiting DataOps and ModelOps in delivering precision within the modern practices of martech, targeting and personalization. In this article and video demonstration, we will cover:
- The recent trend of new analytical techniques and automation coming together to reduce the effort brands need to exhibit to leverage algorithmic scoring in customer interaction management.
- Our perspective on missed opportunities in AI Marketing.
- Explain how SAS Customer Intelligence 360 enables users to execute machine learning and action on the results of champion-challenger modeling pipelines to improve targeting intelligence on websites, mobile apps and more.
- Considerations for critical decisions in balancing marketing objectives between capturing conversions, improving efficiency and maximizing profit.
Before proceeding, the presence of a data science team is not a reality for some brands, and not a full stop solution for others. In the video demonstration below, we will highlight in detail how automation can assist in the challenge of targeting refinement without sacrificing considerations for meeting customizable objectives. Classification modeling, confusion matrices, classifier rules, cut off rates, and other analytical details represent an area of under-exploited potential in martech, and SAS is introducing a user experience that removes barriers in allowing brands to tap into the hype of ModelOps.
Per the Forrester Wave(TM): Customer Analytics Technologies, Q2 2022 report:
"Perhaps most importantly, SAS delivers cutoff recommendations for propensity models to optimize a decision — for example, identifying which customers to contact to optimize conversions while minimizing costs."
Analytical Targeting is the latest feature from SAS Customer Intelligence 360 to automate the use of advanced machine learning enabled by the latest capabilities available from the SAS Viya platform. We are ecstatic to share with you how it works.
We look forward to what the future brings in our development process – as we enable marketing technology users to access all of the most recent SAS analytical developments.
Learn more about how SAS can be applied for customer analytics, journey personalization and integrated marketing here.
